Apparatus, server, system and method for energy measuring

ABSTRACT

Accordingly the embodiments herein provides a method for load balancing in an energy measurement information system. The method includes collecting, by a power information collecting unit, power information at a snapshot extraction frequency. The snapshot extraction frequency is within a range. Further, the method includes detecting, by an operating status extracting unit, an operating status of at least one load apparatus at the snapshot extraction frequency. The operating status is one of a steady state and a transient state. Furthermore, the method includes generating, by a data set generating unit, a data set including only one or a representative snapshot of the power information, when the normal status is detected; and a data set including a plurality of snapshots of the power information, when the transient state is detected.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. application Ser. No.14/526,916, filed Oct. 29, 2014, which claims priority to KoreanApplication No. 10-2014-0018391, filed Feb. 18, 2014, the disclosures ofwhich are incorporated herein by reference. This application also claimspriority to PCT Application No. PCT/KR2015/007234, filed Jul. 13, 2015,which claims priority to Korean Application No. 10-2014-0087330, filedJul. 11, 2014 and Korean Application No. 10-2015-0080222, filed Jun. 5,2015, the disclosures of which are incorporated herein by reference.

TECHNICAL FIELD

The present invention relates to an energy measurement informationsystem, and more particularly, to a system and a method for loadbalancing between an apparatus and a server.

BACKGROUND

A conventional energy measuring apparatus, through an Advanced MeteringInfrastructure (AMI), Automatic Meter Reading (AMR), a digital powermeter, or the like in the prior art, measures only total power usageinformation generated by whole individual load apparatuses associated tothe energy measuring unit. In order to extract energy usage informationof each load apparatus, either multiple energy measuring apparatuses areto be installed or a single energy measuring apparatus with multiplesensors needs to be installed in a distribution board. When an energymeasuring apparatus is installed for each load apparatus, it requiresmore installation space thereby increasing the overall system cost. Whenthe multiple sensors are used in the distribution board, the overallsystem cost increases based on adoption of the multiple sensors.Moreover, there will be a limit in acquiring the energy usageinformation for each of the load apparatuses.

In order to solve the above problems, various mechanisms to efficientlyextract the energy usage information of each load apparatuses at a powerpenetration point are proposed. In one mechanism, a scheme isrepresented to extract the energy usage information of each of the loadapparatuses through a series of computer operations performed formeasuring signal information such as current, voltage, power, and thelike. The measured signal information of each of the load apparatuses isthen directly transmitted to a specific server. However, it is importantto develop an energy measuring apparatus that can perform previoussignal information processing to flexibly process, store, and managemassive data of the server. The previous signal information processingis associated with signal information sampling and clustering of aspecific data set (for example, data corresponding to same loadapparatus). In this case, the processed information needs to maintainresolution at a level to be distinguished for each of the individualload apparatuses while the server computer operates.

Thus, there remains a need of a robust system and method forindividually measuring and labeling energy usage information of aplurality of load apparatus connected to a power penetration point.

SUMMARY OF INVENTION

Accordingly the embodiments herein provide an energy measuringapparatus, at a power penetration point, for load balancing in an energymeasurement information system. The energy measuring apparatus includesa power information collecting unit configured to collect powerinformation at a snapshot extraction frequency. The snapshot extractionfrequency is within a range. The energy measuring apparatus includes anoperating status extracting unit configured to detect an operatingstatus of at least one load apparatus at the snapshot extractionfrequency. The operating status is one of a steady state and a transientstate. Furthermore, the energy measuring apparatus includes a data setgenerating unit configured to generate a data set including arepresentative snapshot of the power information when the normal statusis detected; and generate a data set including a plurality of snapshotsof the power information when the transient state is detected.

In an embodiment, the range is 10 to 900 per second.

In an embodiment, the representative snapshot is selected based on amensuration method.

In an embodiment, the energy measuring apparatus includes a transmittingunit configured to transmit the representative snapshot of the powerinformation, when the normal status is detected; and transmit theplurality of snapshots of the power information, when the transientstate is detected.

In an embodiment, the power information collecting unit is configured tocollect the power information. The power information includes a powersignal at the power penetration point for the plurality of loadapparatuses.

In an embodiment, the snapshot of the power information includes one ofa voltage snapshot and a current snapshot of a waveform having apredetermined cycle as the power information.

Accordingly the embodiments herein provide a server for load managementin an energy measurement information system. The server including acontroller unit configured to compute a signal correlation to reflectpower information of at least one load apparatus based on a snapshot ofpower signal. The snapshot of power signal is related to one of avoltage snapshot and a current snapshot of a waveform having apredetermined cycle measured at a distant energy measuring apparatus.Further, the controller unit is configured to classify the powerinformation based on component units constituting the at least one loadapparatus based on the signal correlation, the power information isclassified as one of an on operation and an off operation. Further, thecontroller unit is configured to generate a data set for the at leastone load apparatus based on the classified power information.

In an embodiment, the one of a multi-steps operation and a continuouschange operation is classified into an association group with one of theon operation and the off operation with respect to same load apparatusbased on the signal correlation.

In an embodiment, the signal correlation includes at least one ofvoltage correlation, current correlation, high-frequency distortion,power signal deformation, active power correlation, and reactive powercorrelation.

In an embodiment, the controller unit is configured to map and recombinethe classified data set according to a time domain; and label therecombined data sets.

In an embodiment, the operating status is used to distinguish adistribution plane for each the load apparatus.

Accordingly the embodiments herein provide an energy measurementinformation system. The energy measurement information system includesan energy measuring apparatus configured to collect power information ata snapshot extraction frequency. The snapshot extraction frequency iswithin a threshold. Further, energy measuring apparatus is configured toextract one of an operating status of at least one of load apparatusesat the snapshot extraction frequency. The operating status is one of asteady state and a transient state; and the apparatus generates andtransmits one of only one or a representative snapshot and a pluralityof snapshots of the power information based on the operating status.Further, the energy measurement information system includes a serverconfigured to compute a signal correlation to reflect the powerinformation of at least one load apparatus based on a snapshot of powersignal. The snapshot of power signal is related to one of a voltagesnapshot and a current snapshot of a waveform having a predeterminedcycle measured at a distant energy measuring apparatus. The server isconfigured to classify the power information based on component unitsconstituting the at least one load apparatus based on the signalcorrelation, the power information is classified as one of an onoperation and an off operation. Further, the server is configured togenerate a data set for the at least one load apparatus based on theclassified power information.

In an embodiment, the server is configured to map and recombine theclassified data set according to a time domain; and label the recombineddata sets.

In an embodiment, the energy measuring apparatus is configured tocollect the power information. The power information includes a powersignal at the power penetration point for the plurality of loadapparatuses.

Accordingly the embodiments herein provide a method for load balancingin an energy measurement information system. The method includescollecting, by a power information collecting unit, a power informationat a snapshot extraction frequency. The snapshot extraction frequency iswithin a range. Further, the method includes detecting, by an operatingstatus extracting unit, an operating status of at least one loadapparatus at the snapshot extraction frequency. The operating status isone of a steady state and a transient state. Furthermore, the methodincludes generating, by a data set generating unit, a data set includinga representative snapshot of the power information, when the normalstatus is detected; and a data set including a plurality of snapshots ofthe power information, when the transient state is detected.

In an embodiment, the snapshot is selected based on a mensurationmethod.

In an embodiment, the method includes transmitting, by a transmittingunit, the representative snapshot of the power information, when thenormal status is detected; and transmitting, by a transmitting unit, theplurality of snapshots of the power information, when the excessivestatus is detected.

In an embodiment, the power information collecting unit is configured tocollect the power information, wherein the power information includes apower signal at the power penetration point for the plurality of loadapparatuses.

In an embodiment, the snapshot of the power information includes one ofa voltage snapshot and a current snapshot of a waveform having apredetermined cycle as the power information.

Accordingly the embodiments herein provide a method for load managementin an energy measurement information system. The method includingcomputing, at a server, a signal correlation to reflect powerinformation of at least one load apparatus based on a snapshot of powersignal, the snapshot of power signal is related to one of a voltagesnapshot and a current snapshot of a waveform having a predeterminedcycle measured at a distant energy measuring apparatus. Further, themethod includes classifying, at the server, the power information basedon component units constituting the at least one load apparatus based onthe signal correlation, the power information is classified as one of anon operation and an off operation. Furthermore, the method includesgenerating, at the server, a data set for the at least one loadapparatus based on the classified power information.

In an embodiment, one of a multi-steps operation and a continuous changeoperation is classified into an association group with one of the onoperation and the off operation with respect to same load apparatusbased on the signal correlation.

In an embodiment, the signal correlation includes at least one ofvoltage correlation, current correlation, high-frequency distortion,power signal deformation, active power correlation, and reactive powercorrelation.

In an embodiment, the method includes mapping and recombining, at theserver, the classified data set according to a time domain; andlabeling, at the server, the recombined data sets.

In an embodiment, the operating status is used to distinguish adistribution plane for each the load apparatus.

These and other aspects of the embodiments herein will be betterappreciated and understood when considered in conjunction with thefollowing description and the accompanying drawings. It should beunderstood, however, that the following descriptions, while indicatingpreferred embodiments and numerous specific details thereof, are givenby way of illustration and not of limitation. Many changes andmodifications may be made within the scope of the embodiments hereinwithout departing from the spirit thereof, and the embodiments hereinincludes all such modifications.

BRIEF DESCRIPTION OF THE FIGURES

This invention is illustrated in the accompanying drawings, throughoutwhich like reference letters indicate corresponding parts in the variousfigures. The embodiments herein will be better understood from thefollowing description with reference to the drawings, in which:

FIG. 1 illustrating a high level overview of a system for managing apower demand and load balancing, according to an embodiment as disclosedherein;

FIG. 2 is a flowchart illustrating a method for managing power usage,according to an embodiment as disclosed herein;

FIG. 3 is a block diagram of a server for managing a power demand,according to an embodiment as disclosed herein;

FIG. 4 is a block diagram of a communicating device for managing thepower demand, according to an embodiment as disclosed herein;

FIGS. 5A and 5B illustrate a screen that outputs guidance information,according to an embodiment as disclosed herein;

FIG. 6 illustrates a screen that outputs compensation information,according to an embodiment as disclosed herein;

FIG. 7 is a block diagram illustrating an energy measuring apparatus ata power penetration point, according to an embodiment as disclosedherein;

FIGS. 8 a, 8 b, and 8 c are flowcharts illustrating various operationsof each component of the energy measuring apparatus at a powerpenetration point, according to an embodiment as disclosed herein;

FIG. 9 a is a flow chart illustrating various operations performed bythe energy measuring apparatus for load management between the energymeasuring apparatus and the server, according to an embodiment asdisclosed herein;

FIG. 9 b is a flow chart illustrating various operations performed bythe server for load management between the energy measuring apparatusand the server, according to an embodiment as disclosed herein;

FIG. 10 is a block diagram illustrating a labeling server, according toan embodiment as disclosed herein;

FIG. 11 is a flowchart illustrating various operation of the labelingserver, according to an embodiment as disclosed herein;

FIG. 12 is a graph illustrating a probability distribution of achievingreduction for a reduction request amount depending on the amount ofcompensation per different unit usage estimated for each subscriber,according to embodiments as described herein;

FIG. 13 a is a flowchart illustrating a method for forecasting powerconsumption based on consumption characteristics, according to theembodiments as described herein;

FIG. 13 b is a flowchart illustrating various operations performed forextracting power consumption element to forecast the power consumptionbased on consumption characteristics, according to the embodiments asdescribed herein;

FIG. 14 is a diagram illustrating an example of calculating acorrelation coefficient, according to the embodiments as describedherein;

FIG. 15 is a diagram illustrating a relationship between powerconsumption for each feeder and a temperature, according to theembodiments as described herein;

FIG. 16 is a diagram illustrating an example for estimating therelationship between the power consumption and the temperature,according to the embodiments as described herein;

FIG. 17 is a diagram illustrating a modeling example, according to theembodiments as described herein;

FIG. 18 is a flowchart illustrating a method for forecasting powerconsumption, according to another exemplary embodiment of the presentinvention; and

FIG. 19 is a block diagram illustrating an apparatus for forecastingpower consumption based on consumption characteristics, according to theembodiments as described herein.

DETAILED DESCRIPTION OF INVENTION

The embodiments herein and the various features and advantageous detailsthereof are explained more fully with reference to the non-limitingembodiments that are illustrated in the accompanying drawings anddetailed in the following description. Descriptions of well-knowncomponents and processing techniques are omitted so as to notunnecessarily obscure the embodiments herein. Also, the variousembodiments described herein are not necessarily mutually exclusive, assome embodiments can be combined with one or more other embodiments toform new embodiments. The term “or” as used herein, refers to anon-exclusive or, unless otherwise indicated. The examples used hereinare intended merely to facilitate an understanding of ways in which theembodiments herein can be practiced and to further enable those skilledin the art to practice the embodiments herein. Accordingly, the examplesshould not be construed as limiting the scope of the embodiments herein.

Prior to describing the present invention in detail, it is useful toprovide definitions for key terms and concepts used herein. Unlessdefined otherwise, all technical and scientific terms used herein havethe same meaning as commonly understood by one of ordinary skill in theart to which this invention belongs.

Request signal: A request signal for power usage reduction may includeinformation on at least one of reduction requirement of powerconsumption for power usage, a reduction required time period, areduction required region, or the like. For example, the request signalmay include information that instructs 10,000 kWh (reduction requiredpower consumption) for 2 P.M. to 5 P.M. on May 1, 2015 (reductionrequired time period). Furthermore, the request signal may includeinformation that designates a specific region (e.g., Suwon-si, Gangnamguof Seoul, or the like) as the reduction required region.

Subscriber information: The subscriber information described herein mayinclude at least one of information on power consumption and predictedconsumption by all load apparatuses or each load apparatus for eachsubscriber, a probability distribution function of reduction for allload apparatuses or each load apparatus by compensation for eachsubscriber, or the like. Further, the subscriber information may includeregistration information on a communicating device, a load apparatus ofthe subscriber, information on a power usage fee for each subscriber, orthe like.

Guidance information: The guidance information of the power usagereduction may include information on at least one of reduced powerconsumption requested for a subscriber (which is selected to request thepower usage reduction), a power usage status of the correspondingsubscriber, the reduction required time period, predicted compensationby reduction, or the like. The guidance information may be provided toall load apparatuses or individual load apparatuses used by thesubscriber.

Compensation Information: The information on compensation for the powerusage reduction may include information on a discount of the power usagefee granted to the corresponding subscriber, points usable at the timeof paying the power usage fee in proportion to actually reduced powerconsumption to correspond to the guidance information, or the like.

The embodiments herein provide a server for managing power demand. Theserver includes a storage unit configured to store subscriberinformation, a receiving unit configured to receive a request signal forpower usage reduction, a selecting unit configured to select asubscriber corresponding to the request signal based on the subscriberinformation, a transmitting unit configured to transmit guidanceinformation for the power usage reduction to a communicating device ofthe subscriber, a monitoring unit configured to monitor the powerconsumption by at least one load apparatus of the selected subscriber,and a compensation managing unit configured to grant a compensation tothe subscriber, when the power consumption by the at least one loadapparatus reduces in accordance to the guidance information.

Accordingly, the embodiments herein achieve an energy measuringapparatus, at a power penetration point, for load balancing in an energymeasurement information system. The energy measuring apparatus includesa power information collecting unit configured to collect powerinformation at a snapshot extraction frequency. The snapshot extractionfrequency is within a range. The energy measuring apparatus includes anoperating status extracting unit configured to detect an operatingstatus of at least one load apparatus at the snapshot extractionfrequency. The operating status is one of a steady state and a transientstate. Furthermore, the energy measuring apparatus includes a data setgenerating unit configured to generate a data set including arepresentative snapshot of the power information when the normal statusis detected; and generate a data set including a plurality of snapshotsof the power information when the transient state is detected.

Accordingly the embodiments herein achieve a server for load managementin an energy measurement information system. The server including acontroller unit configured to compute a signal correlation to reflectpower information of at least one load apparatus based on a snapshot ofpower signal. The snapshot of power signal is related to one of avoltage snapshot and a current snapshot of a waveform having apredetermined cycle measured at a distant energy measuring apparatus.Further, the controller unit is configured to classify the powerinformation based on component units constituting the at least one loadapparatus based on the signal correlation, the power information isclassified as one of an on operation and an off operation. Further, thecontroller unit is configured to generate a data set for the at leastone load apparatus based on the classified power information. In anembodiment, the controller unit is configured to map and recombine theclassified data set according to a time domain; and label the recombineddata sets.

Accordingly the embodiments herein achieve an energy measurementinformation system. The energy measurement information system includesan energy measuring apparatus configured to collect power information ata snapshot extraction frequency. The snapshot extraction frequency iswithin a threshold. Further, energy measuring apparatus is configured toextract one of an operating status of at least one of load apparatusesat the snapshot extraction frequency. The operating status is one of asteady state and a transient state; and generate and transmit one of arepresentative snapshot and a plurality of snapshots of the powerinformation based on the operating status. Further, the energymeasurement information system includes a server configured to compute asignal correlation to reflect the power information of at least one loadapparatus based on a snapshot of power signal. The snapshot of powersignal is related to one of a voltage snapshot and a current snapshot ofa waveform having a predetermined cycle measured at a distant energymeasuring apparatus. The server is configured to classify the powerinformation based on component units constituting the at least one loadapparatus based on the signal correlation, the power information isclassified as one of an on operation and an off operation. Further, theserver is configured to generate a data set for the at least one loadapparatus based on the classified power information. In an embodiment,the server is configured to map and recombine the classified data setaccording to a time domain; and label the recombined data sets.

Accordingly the embodiments herein achieve a method for load balancingin an energy measurement information system. The method includescollecting, by a power information collecting unit, power information ata snapshot extraction frequency. The snapshot extraction frequency iswithin a range. Further, the method includes detecting, by an operatingstatus extracting unit, an operating status of at least one loadapparatus at the snapshot extraction frequency. The operating status isone of a steady state and a transient state. Furthermore, the methodincludes generating, by a data set generating unit, a data set includinga representative snapshot of the power information, when the normalstatus is detected; and a data set including a plurality of snapshots ofthe power information, when the transient state is detected.

Accordingly the embodiments herein achieve a method for load managementin an energy measurement information system. The method includingcomputing, at a server, a signal correlation to reflect powerinformation of at least one load apparatus based on a snapshot of powersignal, the snapshot of power signal is related to one of a voltagesnapshot and a current snapshot of a waveform having a predeterminedcycle measured at a distant energy measuring apparatus. Further, themethod includes classifying, at the server, the power information basedon component units constituting the at least one load apparatus based onthe signal correlation, the power information is classified as one of anon operation and an off operation. Furthermore, the method includesgenerating, at the server, a data set for the at least one loadapparatus based on the classified power information. In an embodiment,the method includes mapping and recombining, at the server, theclassified data set according to a time domain; and labeling, at theserver, the recombined data sets.

Referring now to the drawings and more particularly to FIGS. 1 to 19where similar reference characters denote corresponding featuresconsistently throughout the figures, there are shown preferredembodiments.

FIG. 1 illustrating a high level overview of a system 100 for managingpower demand and load balancing, according to an embodiment as disclosedherein. In an embodiment, the system 100, for managing the power demandand the load balancing, may include an energy measuring apparatus 102 ata power penetration point, a server 104, a communicating device 106, atleast one load apparatus 108 used by the subscriber of the communicatingdevice 106, and a power supply enterprise related server 110.

In an embodiment, the system 100 may be additionally connected with asponsor server 112 and a carbon dioxide emission right transactionserver 114.

The server 104 may include a function of managing the power demand andthe load balancing between the energy measuring apparatus 102 at thepenetration point and the server 104. In an embodiment, the server 104described herein is the same as a labeling server 700 to be described inthe FIG. 7 (in the same configuration as described in the FIG. 1). Inthis case, the server 104 may further include components as comparedwith the labeling server 700 in order to perform the power demandmanaging functions. In an embodiment, the server 104 may be a serverwhich is provided separately from the labeling server 700 in order toperform the power demand managing functions (this may have a separateconfiguration).

The labeling server 700 is not illustrated in the FIG. 1, but it may beassumed that the server 104 performs a function of the labeling server700 (in the case of the same configuration) or the system 100 furtherincludes the labeling server 700 apart from the server 104 (in the caseof the separate configuration).

The communicating device 106 described herein is registered as acommunicating device of a subscriber with the server 104 for datacommunication with the server 104. Some non-limiting examples of thecommunicating device 106 may include mobile apparatus, a smart phone, anotebook, a tablet PC, fixed home appliances (e.g., a TV, arefrigerator, an air-conditioner, or the like), or the like.

In an embodiment, the energy measuring apparatus 102 includes a powerinformation collecting unit configured to collect power information at asnapshot extraction frequency. The snapshot extraction frequency iswithin a range 10 to 900 per second. The energy measuring apparatus 102is configured to detect an operating status of at least one loadapparatus at the snapshot extraction frequency. The operating statusdescribed herein can be one of a steady state and a transient state.Furthermore, the energy measuring apparatus 102 can be configured togenerate a data set including a representative snapshot of the powerinformation when the normal status is detected; and generate a data setincluding a plurality of snapshots of the power information when thetransient state is detected.

Further, in an embodiment, the server 104 is configured to compute asignal correlation to reflect power information of at least one loadapparatus based on a snapshot of power signal. The snapshot of powersignal is related to one of a voltage snapshot and a current snapshot ofa waveform having a predetermined cycle measured at a distant energymeasuring apparatus. Further, the server 104 is configured to classifythe power information based on component units constituting the at leastone load apparatus based on the signal correlation, the powerinformation is classified as one of an on operation and an offoperation. Further, the server 104 is configured to generate a data setfor the at least one load apparatus based on the classified powerinformation.

Furthermore, the server 104 is configured to map and recombine theclassified data set according to a time domain; and label the recombineddata sets.

The FIG. 1 illustrates a limited overview of the system 100 for managingthe power demand and the load balancing between the energy measuringapparatus 102 at the penetration point and the server 104 but, it is tobe understood that other embodiments are not limited thereto. The labelsprovided to each unit, device or component is only for illustrativepurpose and does not limit the scope of the invention. Further, the oneor more unit, device or component can be combined or separated toperform the similar or substantially similar functionalities withoutdeparting from the scope of the invention. Furthermore, the system 100can include various other components interacting locally or remotelyalong with other hardware or software components for managing the powerdemand and the load balancing between the energy measuring apparatus 102at the penetration point and the server 104. For example, the componentcan be, but is not limited to, a process running in the controller orprocessor, an object, an executable process, a thread of execution, aprogram, or a computer.

FIG. 2 is a flowchart illustrating a method for managing power usage,according to an embodiment as disclosed herein. At S202, the methodincludes receiving a request signal for power usage reduction. In anembodiment, the method allows the server 104 to receive the requestsignal for the power usage reduction from the power supply enterpriserelated server 110.

At S204, the method includes selecting the subscriber to whom the server104 would request the power usage reduction. In an embodiment, themethod allows the server 104 to select the subscriber and request thepower usage reduction by using subscriber information with receiving therequest signal. The server 104 described herein may store the subscriberinformation and update the subscriber information by reflecting a powerusage status or pattern of the subscriber, or update the subscriberinformation according to a request by the subscriber.

In an embodiment, the server 104 may select at least one subscriber andrequest the power usage reduction according to a predetermined criterionconsidering power consumption, predicted power consumption, probabilitydistribution of reduction depending on compensation, or the like. Theserver 104 may select a subscriber that is predicted to carry out thepower usage reduction request with minimum cost. Alternatively, theserver 104 may select a subscriber that is predicted to respond to thepower usage reduction request with a high probability. The details aboutthe section of the subscriber are described in conjunction with the FIG.3.

At S206, the method includes transmitting guidance information for powerusage reduction. In an embodiment, the method allows the server 104 totransmit the guidance information for the power usage reduction to thecommunicating device 106 of the subscriber selected in the step (S204).

At S208, the method includes monitoring the power consumption. In anembodiment, the method allows the server 104 to monitor the powerconsumption by at least one load apparatus of the selected subscriber.At S210, the method includes determining whether the actual powerconsumption is reduced and the reduced power consumption in the loadapparatus of the selected subscriber corresponds to the guidanceinformation. In an embodiment, the method allows the server 104 toverify whether the actual power consumption is reduced and the reducedpower consumption in the load apparatus of the selected subscribercorresponds to the guidance information transmitted in the step (S206).The monitoring of the power consumption may be appreciated withreference to the aforementioned description of the collection andextraction of the data regarding the power usage by the labeling server700 as described in the FIG. 7.

At S212, the method includes granting a predetermined compensation tothe corresponding subscriber. In an embodiment, when the server 104determines that the power consumption is reduced to correspond to theguidance information, the server 104 may grant a compensationcorresponding to the power consumption reduction. The server 104 maydecide the compensation to be granted to the corresponding subscriber byconsidering the actual reduced power consumption to correspond to theguidance information.

For example, the server 104 may grant the compensation in proportion tothe reduced power consumption. Further, the server 104 may grant thecompensation for a power consumption fee and grant the compensation as adiscount on the power consumption fee or giving points usable for payingthe power consumption fee.

Alternatively, in an embodiment, the compensation may include cash, agift, a coupon, or the like provided by the sponsor server 112 inaddition to the power supply enterprise related server 110. In thiscase, the server 104 may receive the cash, the gift, the coupon, or thelike from the sponsor server 112 in an electronic form. Alternatively,the server 104 may save conversion points in an electronic form tocorrespond to the cash, the gift, or the coupon received from a sponsorin an account of the corresponding sponsor. The server 104 calculatesthe reduced power consumption corresponding to the cash, the gift, thecoupon, or the conversion points received for each sponsor. Further, thesponsor server 112 may acquire a carbon dioxide emission right from thecarbon dioxide emission right transaction server 114 based on thecalculated reduced power consumption. In this case, ‘based on thereduced power consumption’ may non-exclusively refers to all cases inwhich the reduced power consumption is converted into a reduced carbondioxide amount based on the reduced power consumption and those skilledin the art may convert the reduced power consumption into a reducedcarbon dioxide amount by using the conventional method known or to beknown in the art. Further, the carbon dioxide emission right transactionserver 114 may verify that the power is reduced as much as the cash, thegift, the coupon, or the like provided by the sponsor server 112 fromthe power supply enterprise related server 110 or the server 104.

Further, at S214, the method includes transmit information regarding thecompensation to the communicating device 106. In an embodiment, themethod allows the sever 104 to transmit compensation information aboutthe granted compensation to the communicating device 106 of thecorresponding subscriber. The subscriber of the communicating device 106may verify whether the actual power consumption fee is discounted by auser power reduction act and a discount degree. This may show an effectof inducing the subscriber to positively participate in reducing thepower at a time when the power reduction is required.

Unlike the conventional systems and methods, a power usage reductionscheme based on a non-intrusive load monitoring for power usage of asubscriber can be implemented without construction of an expensivesystem for the power usage reduction. Further, the power usage reductionis performed by considering a time period in which the power usagereduction is required. The power usage reduction is induced for asubscriber which can carry out the given power usage reduction withminimum cost to increase power reduction efficiency. The power usagereduction is compensated to induce the subscriber to positivelyparticipate in the power usage reduction. Furthermore, the proposedsystem and method can be implemented using existing infrastructure andmay not require extensive setup and instrumentations.

The various actions, acts, blocks, steps, or the like of the FIG. 2 maybe performed in the order presented, in a different order orsimultaneously. Further, in some embodiments, some of the actions, acts,blocks, steps, or the like may be omitted, added, modified, skipped, orthe like without departing from the scope of the invention.

FIG. 3 is a block diagram of the server 104 for managing the powerdemand and the load balancing, according to an embodiment as disclosedherein. In an embodiment, the server 104 may include a storage unit 302storing the subscriber information, a receiving unit 304 receiving therequest signal for the power usage reduction, a transmitting unit 306transmitting the guidance information for the power usage reduction tothe communicating device of the selected subscriber, a selection unit308 selecting the subscriber and request the power usage reduction byusing the subscriber information with receiving the request signal, amonitoring unit 310 monitoring the power consumption by the loadapparatus of the selected subscriber, and a compensation managing unit312 granting a predetermined compensation to the correspondingsubscriber when the power consumption by the load apparatus is reducedaccording to the guidance information.

The receiving unit 304 and the transmitting unit 306 may be implementedas respective units or one communication unit 314. Further, theselection unit 308, the monitoring unit 310, and the compensationmanaging unit 312 may be implemented as respective units or one controlunit 316.

The receiving unit 304 and the transmitting unit 306 may be implementedas respective modules or one communication module 314. Further, theselection unit 308, the monitoring unit 310, and the compensationmanaging unit 312 may be implemented as respective modules or onecontrol module 316.

The storage unit 302 may store the subscriber information and inparticular, store information on the power usage for each subscriber.For example, the storage unit 302 may store, as the subscriberinformation, information on the power consumption by all the loadapparatuses or an individual load apparatuses for each subscriber, atemporal power usage profile, a power reduction history according to theguidance information, or the like. In more detail, the power reductionhistory according to the guidance information may include informationregarding whether the power consumption is actually reduced, the reducedpower consumption, a load apparatus that reduces the power consumption,or the like to correspond to the previous guidance information includingthe compensation method and the amount of compensation.

The receiving unit 304 may receive the request signal for the powerconsumption reduction from the power supply enterprise related server110 before the start of a time period when the power usage reduction isrequired.

For example, the power supply enterprise related server 110 may transmitthe request signal one week, one day, or one hour before the start ofthe time period when the power usage reduction is required. This is usedto induce the positive power usage reduction act by providing theguidance information for the power usage reduction to the subscriberbefore the time period when the power usage reduction is required.

The selecting unit 308 may select at least one subscriber to whom theserver 104 would request the power usage reduction according to apredetermined criterion considering the power consumption, the temporalpower consumption, the probability distribution of the reductiondepending on the compensation, or the like. Therefore, the server 104may select a subscriber that is predicted to carry out the power usagereduction request with minimum cost. Alternatively, the server 104 mayselect a subscriber that is predicted to respond to the power usagereduction request with the highest probability.

For example, the selecting unit 308 may select at least one subscriberso as to reduce the power usage with the minimum cost by considering apower consumption degree at the reduction required time period, aprediction value of the power consumption at the reduction required timeperiod, a response rate to the existing power usage reduction or reducedpower consumption, the probability distribution of the reductiondepending on the compensation, or the like. In an embodiment, theprobability distribution of the reduction depending on the compensationmay be estimated based on the actual reduced power consumption for thepast power usage reduction request. Further, a usage change of a userfor a fee change depending on a progressive accumulation step may alsobe used to generate a probability distribution of the reduction by thecompensation. The probability distribution of achieving a reductionobject depending on the compensation may vary depending on the predictedpower consumption for each load apparatus or of all the load apparatusesat a reduction target time. An example graph illustrating a probabilitydistribution of achieving reduction for a reduction request amountdepending on the amount of compensation per different unit usageestimated for each subscriber is described in conjunction with the FIG.12.

The selecting unit 308 calculates the unit amount of compensation tosatisfy the reduction required power consumption with the minimum costand the amount Δi of reduction request for each of the individual users(i=1, . . . n). The amount of compensation is calculated by consideringa probability distribution Fi (Δ;p) of reduction depending oncompensation configured for each of individual users with respect toreduced request power consumption W and the amount p of compensation perunit usage included in the request signal.

Find Δi, p

that minimizes

$\sum\limits_{i}{\Delta_{i} \times p}$

such that

$ W \middle| {\sum\limits_{i}{\Delta_{i} \times {F_{i}( {\Delta_{i};p} )}}} $

Herein, a probability distribution function of the reduction isestimated for each of the individual apparatuses to calculate the amountof reduction request for each of the individual apparatuses.Alternatively, the selecting unit 308 may select the subscriber so thatexpectation values of the response rate for each subscriber or eachsubscriber load apparatus and the usage reduction history satisfy thereduction required power consumption included in the request signal.

Further, the selecting unit 308 may select the subscriber by calculatingthe anticipated reduction required power consumption, which is more thanthe reduction required power consumption included in the request signalby a predetermined amount. This is to provide against the presence of asubscriber that does not participate in the power reduction among theselected subscribers.

For example, the selecting unit 308 may select the subscriber so thattotal anticipated reduction required power consumption becomes 20,000kWh by considering power consumption at 2 P.M., and response rate and areduction amount depending on the previous guidance information whenreceiving the request signal (requesting reduction of 10,000 kW at 2P.M. tomorrow). In this case, the selecting unit 308 calculates twicethe reduction required power consumption included in the request signalas the anticipated reduction required power consumption to select thesubscriber based on the calculated anticipated reduction required powerconsumption when the power reduction response rate for the existingguidance information is 50%.

Further, the selecting unit 308 may select the subscriber to whom theserver 104 would request the power usage reduction except for asubscriber that generally uses basic power during the reduction requiredtime period. Herein, the basic power may mean stand-by power of the loadapparatus or minimum power for maintaining an activation state. When apower reduction possibility of a load apparatus using only the basicpower is very low, the selecting unit 308 may exclude the correspondingload apparatus from as elected target of the power reduction.

For example, the selecting unit 308 calculates a power value acquired bysubtracting basic power consumption from the predicted power consumptionduring the time period. This requires the power usage reduction withrespect to all subscribers and determines the calculated power value asreduced power consumption to calculate the anticipated reductionrequired power consumption, and reduction required power consumption foreach reduction required subscriber and each subscriber within reduciblepower consumption.

Further, when the selected subscriber uses multiple load apparatuses,the selecting unit 308 may decide total reduced power consumptionrequired for the selected subscriber, and the reduction required powerconsumption for each power reducible load apparatus or each loadapparatus.

In addition, when information on a specific region in which the powerreduction is required is included in the request signal, the selectingunit 308 may select a subscriber that to whom the server 104 wouldrequest the power reduction among subscribers that reside in thespecific region.

The transmitting unit 306 may transmit guidance information for thepower usage reduction to the communicating device 106 of the subscriberselected by the selecting unit 308.

For example, the guidance information may include the time period inwhich the power reduction is required, the reduction required powerconsumption, reducible power consumption for all the load apparatuses orthe individual load apparatuses, a guide (e.g., lower a temperature ofan air-conditioner to a predetermined temperature, increase a freezingor refrigeration temperature of a refrigerator, unplug from a socket ofan unused electronic product, or the like) for the power usagereduction, compensation information depending on the power usagereduction, or the like.

The monitoring unit 310 may monitor the power consumption by the loadapparatus of the selected subscriber after transmitting the guidanceinformation. This is to determine whether the power consumption by theload apparatus of the subscriber is actually reduced or a degree of thereduced power consumption to correspond to the guidance information andgrant the compensation.

When the power consumption by the load apparatus of the selectedsubscriber is reduced according to the transmitted guidance information,the compensation managing unit 312 may grant a predeterminedcompensation to the corresponding subscriber in proportion to thereduced power consumption. In more detail, the compensation managingunit 312 may grant the compensation for the power consumption fee.

For example, the compensation managing unit 312 may grant thecompensation by providing discount on the power consumption fee or bygiving the points usable for paying the power consumption fee.Alternatively, the compensation managing unit 312 may grant the cash,the gift, the coupon, or the like received from the sponsor server 112as the compensation.

Furthermore, the transmitting unit 306 may transmit information(hereinafter, referred to as reduction information) on the powerreduction according to the guidance information for each subscriber tothe power supply enterprise related server 110. The power supply relatedserver 110 may decide a compensation corresponding to whether the poweris reduced and the reduced power consumption included in the reductioninformation and transmit information on the decided compensation to theserver 104. Therefore, the compensation managing unit 312 may grant thecompensation for the corresponding subscriber based on the informationon the compensation received from the power supply related server 110.

Meanwhile, the compensation managing unit 312 may previously define acompensation grant criterion based on whether the power is reduced andthe reduced power consumption according to the guidance information andgrant the compensation for the corresponding subscriber based on thecompensation grant criterion.

The transmitting unit 306 may transmit information (hereinafter,referred to as compensation information) regarding the grantedcompensation to the communicating device 106 of the correspondingsubscriber.

Further, in an embodiment, the controller unit 316 is configured tocompute a signal correlation to reflect power information of at leastone load apparatus based on a snapshot of power signal, wherein thesnapshot of power signal is related to one of a voltage snapshot and acurrent snapshot of a waveform having a predetermined cycle measured ata distant energy measuring apparatus. Further, the controller unit 316is configured to classify the power information based on component unitsconstituting the at least one load apparatus based on the signalcorrelation, wherein the power information is classified as one of an onoperation and an off operation. Further, the controller unit 316 isconfigured to generate a data set for the at least one load apparatusbased on the classified power information. Further, the controller unit316 is configured to map and recombine the classified data set accordingto a time domain; and label the recombined data sets.

The FIG. 3 illustrates a limited overview of the server 104 for managinga power demand based but, it is to be understood that other embodimentsare not limited thereto. The labels provided to each unit or module isonly for illustrative purpose and does not limit the scope of theinvention. Further, the one or more units or modules can be combined orseparated to perform the similar or substantially similarfunctionalities without departing from the scope of the invention.Furthermore, the server 104 can include various other componentsinteracting locally or remotely along with other hardware or softwarecomponents to manage the power demand.

FIG. 4 is a block diagram of the communicating device 106 for managingthe power demand, according to an embodiment as disclosed herein. In anembodiment, the communicating device 106 may include a communicationunit 402 receiving guidance information for the power usage reductionfrom the server 104, a control unit 404 executing a power relatedapplication with receiving the guidance information, and an output unit406 outputting the guidance information by executing the power relatedapplication. Further, the communicating device 106 may further include astorage unit 410 storing the power related application, the guidanceinformation, the compensation information, or the like.

The control unit 404 may control an operation of at least one of thecommunication unit 402, the output unit 406, an input unit 408, and thestorage unit 408. The power related application means an application formanaging power usage of the load apparatuses possessed by a subscriberof the communicating device 106 and may be installed while producing thecommunicating device 106 or installed by being downloaded from anexternal server by subscriber's selection.

The control unit 404 may automatically execute the power relatedapplication or execute the power related application only when providinga guidance information receiving notice to the subscriber andthereafter, receiving an execution command from the subscriber, whenreceiving the guidance information.

For example, the guidance information receiving notice may express abrief content of the guidance information and outputvibration/lamp/notice sound for just notifying whether to receive theguidance information. The output of the guidance information isdescribed in conjunction with the FIGS. 5A and 5B.

Further, the communication unit 402 may receive the information(hereinafter, referred to as compensation information) regarding thecompensation granted to correspond to the power usage reductionaccording to the guidance information from the server 104 and the outputunit 406 executes the power related application to output the receivedcompensation information. The output of the compensation information isdescribed in conjunction with the FIG. 6.

Since the receiving notice of the compensation information may bedescribed by citing the description of the receiving notice of theguidance information, a detailed description thereof will be omitted forthe sake of brevity.

Further, the communicating device 106 may further include the input unit408 receiving a power reduction command for at least one load apparatusby executing the power related application. The communication unit 402may transmit the power reduction command signal to a load apparatus 108corresponding to the power reduction command.

For example, the communicating device 106 may receive a command orselection associated with an operation control (e.g., power on/off, atemperature control of the air-conditioner/refrigerator, or the like)for each load apparatus from the subscriber through the input unit 408.In more detail, the input unit 408 may receive selection of a loadapparatus of which power is intended to be reduced from the subscriberor receive a power reduction method for each load apparatus.

The load apparatus 108 may reduce power consumption to correspond to apower reduction command signal when receiving the power reductioncommand signal. In an embodiment, the load apparatus 108 may transmit aresponse (hereinafter, referred to as a response signal) to whether apower reduction operation is performed to correspond to the powerreduction command signal to the communicating device 106.

For example, when the load apparatus 108 is a refrigerator and the powerreduction command signal includes a recommended freezing orrefrigeration room temperature for a predetermined time, the recommendedfreezing or refrigeration room temperature may be maintained for apredetermined time. Alternatively, when the load apparatus 108 is acomputer and the power reduction command signal includes a power offcommand, power of the computer may be turned off.

The FIG. 5 illustrates a limited overview of the communication device106 for managing a power demand based but, it is to be understood thatother embodiments are not limited thereto. The labels provided to eachunit are only for illustrative purpose and does not limit the scope ofthe invention. Further, the one or more units can be combined orseparated to perform the similar or substantially similarfunctionalities without departing from the scope of the invention.Furthermore, the communication device 106 can include various othercomponents interacting locally or remotely along with other hardware orsoftware components to manage the power demand.

FIGS. 5A and 5B illustrate a screen that outputs guidance informationfor power consumption reduction according to the embodiment of thepresent invention. Herein, it is assumed that the guidance informationmay be output when executing the power related application.

FIGS. 5A and 5B illustrate a screen that outputs guidance information,according to an embodiment as disclosed herein. According to the FIG.5A, the communicating device 106 may display a screen including a timeperiod (2:30 P.M. to 3:00 P.M.) in which the power usage reduction isrequired and anticipated compensation information (saving saved money of5,000 points) depending on the power usage reduction as the guidanceinformation.

According to the FIG. 5B, the communicating device 106 displays astatement list which the subscriber achieves according to the guidanceinformation of the power consumption reduction and the amount ofcompensation therefore to motivate the user to more positivelyparticipate in reducing the power consumption.

FIG. 6 illustrates a screen that outputs compensation information forpower usage reduction, according to an embodiment as disclosed herein.It is assumed that the compensation information may be output whenexecuting the power related application. According to the FIG. 6, whenthe communicating device 106 acquires points (hereinafter, referred toas compensation points) usable for paying the power consumption fee tocorrespond to the power usage reduction, the communicating device 106may display the acquired compensation point (e.g., 3200 points) andpresent a method that can encash the acquired compensation point.Furthermore, the communicating device 106 may display a total amount(e.g., 777,777,777 won) acquired by converting the compensation pointinto the cash and a ranking (e.g., 37th) of a subscriber of thecommunicating device 106 among all the subscribers.

Hereinafter, referring to the FIGS. 7 to 10, an energy measuringapparatus at a penetration point of power and a labeling server 700generating power information by labeling a data set received therefrom,according to an embodiment of the present invention will be described.

FIG. 7 is a block diagram illustrating an energy measuring apparatus 102at a power penetration point, according to an embodiment as disclosedherein. In the embodiment, the energy measuring apparatus 102 can beconfigured to generate an unregistered load clustering data set in orderto individually estimate energy consumption information of each loadapparatus connected to the power penetration point and transmits theestimated energy consumption information to an energy measurementinformation labeling server 700.

The energy measuring apparatus 102 described herein is installedtogether with a single sensor at the power penetration point. The energymeasuring apparatus 102 performs a series of operations to measure totalelectric energy consumption and estimate energy consumption of each loadapparatus. Unlike the conventional systems and methods, a previousinformation processing process performed for each load apparatus issummarized below.

First, a snapshot is extracted from a signal of voltage or current.Noise filtering is performed by extracting a reference point. Normal orexcessive statuses of the voltage, active power, reactive power, or thelike are distinguished based on a corresponding result, and operatingstatuses. An operating status change such as an on or off event of theindividual load apparatuses are extracted through the distinguishednormal or excessive statuses. In addition, a final clustering data setis generated by pattern matching load classification through avoltage-current correlation, a high-frequency distortion, a current orpower snapshot signal deformation, an active or reactive powercorrelation, or the like associated with a load feature. Further, thegenerated clustering data set is transmitted to the energy measurementinformation labeling server 700 or cloud through data compression in anunregistered status. For example, load classification mark such as 1, 2,3 or A, B, C, or the like may not be a registered status and may not berecognized to a user.

The energy measuring apparatus 102 can include a power informationcollecting unit 702, an operating status extracting unit 704, a data setgenerating unit 706, and a transmitting unit 708.

In an embodiment, the power information collecting unit 702 can beconfigured to collect energy or power information including a powersignal at the power penetration point for a plurality of loadapparatuses. The load apparatus described herein can include energyusing apparatuses or components using electric energy. In an embodiment,the load apparatus can include both the individual energy apparatus suchas television, refrigerator, or the like and the component unit such asmotor, light, or the like. The power penetration point can be, forexample, a node into which power penetrates with respect to theplurality of load apparatuses such as the power penetration point of apanel board or a distribution board of a household. Further, the variousoperations performed by the power information collecting unit 702 aredescribed in detail in conjunction with the FIG. 8 a.

In an embodiment, the operating status extracting unit 704 can beconfigured to distinguish between a normal or excessive status of apower change from the collected voltage or power information to extractan operating status or a change pattern of the operating status of theload apparatus. Further, the various operations performed by theoperating status extracting unit 704 are described in detail inconjunction with the FIG. 8 b.

In an embodiment, the data set generating unit 706 can be configured togenerate a data set for each of the individual load apparatuses whichmatches the operating status or the change pattern of the operatingstatus through a signal correlation depending on power usage informationof the individual load apparatuses. The various operations performed bythe data set generating unit 706 are described in detail in conjunctionwith the FIG. 8 c.

When the data sets are generated, the transmitting unit 708 can beconfigured to transmit the generated data sets to the energy measurementinformation labeling server 700 that generates labeled power informationby recombining the data sets.

In an embodiment, the energy measuring apparatus 102, at the powerpenetration point, for load balancing between the energy measuringapparatus 102 and the server 104 is described. The power informationcollecting unit 702 is configured to collect power information at asnapshot extraction frequency. The snapshot extraction frequencydescribed herein within a range of 10 to 900 per second. The operatingstatus extracting unit 704 is configured to detect an operating statusof at least one load apparatus at the snapshot extraction frequency. Theoperating status described herein is one of a steady state and atransient state. Further, the data set generating unit 706 is configuredto generate a representative snapshot of the power information, when thenormal status is detected. The data set generating unit 706 isconfigured to generate a plurality of snapshots of the powerinformation, when the transient state is detected. Furthermore, thetransmitting unit 708 is configured to transmit the representativesnapshot of the power information, when the normal status is detected;and transmit all the snapshots of the power information, when thetransient state is detected. Furthermore, the various operationsperformed for load management between the server 104 and the energymeasuring apparatus 102 is described in conjunction with the FIG. 9.

The FIG. 7 illustrates a limited overview of the energy measuringapparatus 102 but, it is to be understood that other embodiments are notlimited thereto. The labels provided to each unit or component is onlyfor illustrative purpose and does not limit the scope of the invention.Further, the one or more modules can be combined or separated to performthe similar or substantially similar functionalities without departingfrom the scope of the invention. Furthermore, the energy measuringapparatus 102 can include various other components interacting locallyor remotely along with other hardware or software components to measureenergy usage information of a plurality of load apparatus connected to apower penetration point. For example, the component can be, but is notlimited to, a process running in the controller or processor, an object,an executable process, a thread of execution, a program, or a computer.

FIG. 8 a is a flowchart illustrating various operations performed by thepower information collecting unit 702 of the energy measuring apparatus102 at a power penetration point, according to the embodiments asdescribed herein. In the embodiment, the power information collectingunit 702 can be configured to measure a power signal (Step S802).Unprocessed power information waveforms of the current and the voltageare measured through the energy measuring apparatus 102 installed at thepower penetration point and the single sensor.

Further, the power information collecting unit 702 can be configured toextract snapshot (Step S804). A voltage or current snapshot of an ACwaveform having a predetermined cycle is collected. In the embodiment,snapshots of voltage having one AC cycle waveform and high-frequencycurrent are preferably extracted.

FIG. 8 b is a flowchart illustrating various operations performed by theoperating status extracting unit 704 of the energy measuring apparatus102 at a power penetration point, according to the embodiments asdescribed herein. The operating status extracting unit 704 can beconfigured to distinguish between a normal or excessive status of apower change from the collected voltage or power information to extractan operating status or a change pattern of the operating status of theload apparatus.

Referring to the FIG. 8 b, the operating status extracting unit 704 canbe configured to extract power information and reference point (StepS806). In an embodiment, real-time power consumption and power qualityinformation are extracted, and the reference point for distinguishingthe normal or excessive status is extracted.

In the embodiment, the reference point is preferably power consumptionwhich is constantly used without fluctuation while being not turned onor off and continuously turned on in each of the load apparatusesthrough the extraction of the real-time power consumption and powerquality information.

Further, the operating status extracting unit 704 can be configured toseparate an excessive response (Step S808). In an embodiment, anexcessive status interval is extracted, in which turn-on or off isperformed or the operating status is changed by operations of theindividual load apparatuses in the power consumption.

Furthermore, in an embodiment, the operating status extracting unit 704can be configured to remove a noise (Step S810). A meaninglesshigh-frequency noise signal generated in power signal measurement oftotal power consumption is removed.

Furthermore, the operating status extracting unit 704 can be configuredto classify the snapshot according to the extracted operating status orchange pattern of the operating status. For example, in the case ofbeing determined as the excessive response operation, the snapshot mayhave an even higher snapshot extraction frequency than the normalstatus.

Furthermore, the operating status extracting unit 704 can be configuredto detect an on or off event (Step S812). In an embodiment, thesnapshots for events are classified for each on or off status beforeclustering each of the individual load apparatuses through detection ofthe on or off event. The operating status extracting unit 704 can beconfigured to detect status change (Step S814). Multi-steps other thanthe on or off operation are provided. The change patterns of theoperating statuses of loads which have a continuous changecharacteristic are detected and classified.

After detecting the status change, the operating status extracting unit704 can be configured to process real-time total power consumption data(Step S816). In an embodiment, the power information data is operatedand stored, and a transmission data packet is generated with respect tototal energy consumption and the power quality information for areal-time power consumption service.

FIG. 8 c is a flowchart illustrating various operations performed by thedata set generating unit 706 of the energy measuring apparatus 102 at apower penetration point, according to the embodiments as describedherein. The data set generating unit 706 can be configured to generate adata set for each of the individual load apparatuses which matches theoperating status or the change pattern of the operating status through asignal correlation depending on power usage information of theindividual load apparatuses.

Referring to the FIG. 8 c, the data set generating unit 706 extractsload features (Step S820). In the embodiment, a signal correlation, onwhich the power usage features of the individual load apparatuses arereflected, is generated by using the snapshot, the excessive response,the on or off event, and the status change information extracted fromthe total power consumption data. The signal correlation can include thevoltage or current correlation, the high-frequency distortion, thecurrent or power signal deformation, the active or reactive powercorrelation, or the like.

Further, the data set generating unit 706 can be configured to match theon or off event (Step S822), and classify pattern matching load (StepS824) to generate the data set. The on or off operation events for theindividual load apparatuses are classified in a pair of the same loadapparatuses based on the generated signal correlation. The multi-stepsor continuous change characteristics are classified into an associationgroup with the on or off operation events with respect to the same loadapparatus based on the generated signal correlation.

Furthermore, the data set generating unit 706 can be configured togenerate a data set (Step S826). The data sets collected by theassociation group are generated through the on or off event matching andthe pattern matching load classification.

When the data sets are generated, the transmitting unit 708 can beconfigured to transmit the generated data sets to the energy measurementinformation labeling server 700 that generates labeled power informationby recombining the data sets.

Prior to the transmission, in the embodiment, the data packet generatedby the energy measuring apparatus 102 is compressed to facilitatetransmission of the massive data to the energy measurement informationlabeling server 700.

Further, the power consumption and the quality information data requiredto perform a real-time power energy information service can be togethertransmitted.

Further, referring to the FIGS. 8 a to 8 c, a snapshot extraction (thatis, power signal sampling) period and the resulting informationprocessing efficiency of the present invention will be described indetail.

In an embodiment, it is important for the power information collectingunit 702 to appropriately select the snapshot extraction frequency. Whena snapshot extraction frequency is lower than a specific value, forexample, when the snapshot extraction frequency is less than once persecond, a resolution for a transient state interval of the loadapparatus is low. As a result, it is difficult to distinguish differentindividual load apparatuses. When the snapshot extraction frequency ishigher than a specific value, for example, when the snapshot extractionfrequency is higher than thousands to ten thousand times per second, theresolution for the transient state interval is excessively high. As aresult, an error may occur, such as recognizing the same loadapparatuses as different load apparatuses. Therefore, the snapshotextraction frequency for efficient prior information processing of theenergy measuring apparatus at the penetration point of power isappropriately 10 to 900 times per second.

Further, information processing after extracting the operating state maybe efficient through the snapshot classification of the operating statusextracting unit 704 (e.g., a method in which, in the snapshot extractionstep (S804), the snapshot is continuously extracted at 15 times persecond. But when there is no change in operating status, only onesnapshot among 15 snapshots or a representative value is selected andclassified. When the change in operating status is sensed, all of the 15snapshots are selected to separately increase only the resolution of thetransient state interval). That is, by a method in which while theresolution of the transient state interval (which is required for theenergy usage information analysis) for each apparatus increases, a datatraffic related burden decreases (e.g., even in the case where thetransmitting unit 708 periodically transmits data once per second, whenthere is no change in operating status, only one snapshot which isselected and classified, or the representative value calculated throughmensuration of division is transmitted. During the transient stateinterval, 15 snapshots are transmitted at once). Whole system'scapability of load balancing between the energy measuring apparatus 102and the server 104 is improved. As a result, the on or off eventdetecting step (S812), the stats change detecting step (S814), and someor all the steps performed by the data set generating unit 706 may beperformed through the server 104.

The details of the energy measurement information labeling server 700that generates the labeled power information by receiving the data setsgenerated by the power penetration point energy measuring apparatus 102are described in conjunction with the FIG. 10.

The various actions, acts, blocks, steps, or the like of the FIG. 8 maybe performed in the order presented, in a different order orsimultaneously. Further, in some embodiments, some of the actions, acts,blocks, steps, or the like may be omitted, added, modified, skipped, orthe like without departing from scope of the invention.

FIG. 9 a is a flow chart illustrating various operations performed bythe energy measuring apparatus 102 for load management between theenergy measuring apparatus 102 and the server 104, according to anembodiment as disclosed herein. At S902, the method includes collectingpower information at a snapshot extraction frequency, wherein thesnapshot extraction frequency is within a range. In an embodiment, therange described herein is within 10 to 900 times per second. Unlike theconventional systems and methods, an appropriate snapshot extractionfrequency selected for the efficient prior information processing of theenergy measuring apparatus at the penetration point of power. Forexample, when the snapshot extraction frequency is lower than a specificvalue, for example, when the snapshot extraction frequency is less thanonce per second, a resolution for a transient state interval of the loadapparatus is low. As a result, it is difficult to distinguish differentindividual load apparatuses. When the snapshot extraction frequency ishigher than a specific value, for example, when the snapshot extractionfrequency is higher than thousands to ten thousand times per second, theresolution for the transient state interval is excessively high. As aresult, an error may occur, such as recognizing the same loadapparatuses as different load apparatuses. Therefore, the snapshotextraction frequency for efficient prior information processing of theenergy measuring apparatus at the penetration point of power isappropriately 10 to 900 times per second.

At S904, the method includes detecting an operating status of loadapparatus at the snapshot extraction frequency. In an embodiment, theoperating status described herein is one of a steady state and atransient state. At S906, the method includes generating a data setincluding a representative snapshot of the power information, when thenormal status is detected; and generating a data set including aplurality of snapshots of the power information, when the transientstate is detected as shown at S908. For example, the snapshot iscontinuously extracted at 15 times per second. But when there is nochange in operating status, only one snapshot among 15 snapshots or arepresentative value is selected and classified. When the change inoperating status is sensed, all of the 15 snapshots are selected toseparately increase only the resolution of the transient stateinterval). Unlike the conventional systems and methods, the snapshot isselected based on a mensuration method. That is, by a method in whichwhile the resolution of the transient state interval (which is requiredfor the energy usage information analysis) for each apparatus increases,a data traffic related burden decreases (e.g., even in the case wherethe transmitting unit 708 periodically transmits data once per second,when there is no change in operating status, only one snapshot which isselected and classified, or a representative value calculated throughmensuration of division is transmitted. During the transient stateinterval, 15 snapshots are transmitted at once). Whole system'scapability of load balancing between the energy measuring apparatus 102and the server 104 is improved. As a result, the on or off eventdetecting step (S812), the stats change detecting step (S814), and someor all the steps performed by the data set generating unit 706 may beperformed through the server 104 as described in the FIG. 9 b.

FIG. 9 b is a flow chart illustrating various operations performed bythe server 104 for load management between the energy measuringapparatus 102 and the server 104, according to an embodiment asdisclosed herein. At S910, the method includes computing a signalcorrelation to reflect power information of the load apparatus based ona snapshot of power signal. In an embodiment, the method allows theserver 104 to compute the signal correlation to reflect powerinformation of the load apparatus based on the snapshot of the powersignal. The signal correlation described herein includes at least one ofvoltage correlation, current correlation, high-frequency distortion,power signal deformation, active power correlation, and reactive powercorrelation. The snapshot of the power signal described herein isrelated to one of a voltage snapshot and a current snapshot of awaveform having a predetermined cycle measured at a distant energymeasuring apparatus.

At S912, the method includes classifying the power information based oncomponent units constituting the apparatus 104 based on the signalcorrelation. In an embodiment, the method allows the server 104 to matchthe on or off event and classify pattern matching load to generate thedata set. The on or off operation events for the individual loadapparatuses are classified in a pair of the same load apparatuses basedon the generated signal correlation. The multi-steps or continuouschange operation are classified into an association group with the onoperation or off operation events with respect to the same loadapparatus based on the generated signal correlation.

At S914, the method includes generating a data set for each apparatusbased on the classified power information. In an embodiment, the datasets collected by the association group are generated through the on oroff event matching and the pattern matching load classification.

At S916, the method may include detecting an operating status of theload apparatus at the snapshot extraction. The method allows the server104 detect the operating status of the load apparatus at the snapshotextraction. A distribution plane is distinguished according to loadoperating characteristics (on or off, multi-steps, a continuous change,always activation, or the like) for the individual load apparatusesdetermined as the same energy load apparatus.

At S918, the method includes mapping and recombining the classified dataset according to a time domain. In an embodiment, the method allows theserver 104 to map and recombine the classified data set according to thetime domain. At S920, the method includes labeling the recombined datasets.

The various actions, acts, blocks, steps, or the like of the FIG. 9 maybe performed in the order presented, in a different order orsimultaneously. For example, the step of generating a data set at S914may comprise the step of mapping and recombining the classified data setat S918 and the step of labeling the recombined data set at S920.Further, in some embodiments, some of the actions, acts, blocks, steps,or the like may be omitted, added, modified, skipped, or the likewithout departing from scope of the invention.

The FIG. 10 is a block diagram illustrating the energy measurementinformation labeling server 700, according to the embodiments asdescribed herein. In an embodiment, the energy measurement informationlabeling server 700 can be configured to process the energy usageinformation and saving tip consulting for a power user at the powerpenetration point through processes such as machine running andautomatic labeling based on the received clustering data set andreal-time power consumption, and power quality information data set. Theenergy measurement information labeling server 700 may be a mass dataprocessing device that processes the total energy information and energyinformation for each of the individual load apparatuses to generatevarious energy saving solutions.

In an embodiment, the energy measurement information labeling server 700can be configured to process specific post information through thevarious computer operations. The process classifies the unregisteredload clustering data set into multi-dimensional planes based on thereference area, such as the active power, the reactive power, the time,or the like. The process sets a classification boundary surface in thesame load apparatus through the machine running to distinguish theunregistered load clustering set for each specific operation orcomponent such as on or off, multi-steps, continuous change,always-activation, or the like.

The distinguished data sets are mapped to the real-time powerconsumption change to complete the distinguishment and the lowercomponents of the individual load apparatuses are grouped into the sameload apparatus which may be recognized by the user (1+2+3 or A+B+C).Further, the registered data sets (refrigerator, washing machine,air-conditioner, or the like) of the individual load apparatuses arematched which have been already stored to be automatically labeled.

In this case, the load apparatuses which are not automatically labeleddue to data which are present in the registered data sets are manuallylabeled through a means of checking the corresponding time by manuallyturning on or off the load apparatuses which are not automaticallylabeled. In addition, the manually generated data are added to thepre-collected data set again and then used for the automatic labeling.Further, the various components of the energy measurement informationlabeling server 700 and operations thereof are described in conjunctionwith the FIG. 11.

Referring to the FIG. 10, in an embodiment, the energy measurementinformation labeling server 700 can include a receiving unit 1002, arecombining unit 1004, and a labeling unit 1006.

The receiving unit 1002 can be configured to receive a data setgenerated by classifying power information based on individual loadapparatuses. The recombining unit 1004 can be configured to classify thereceived data set on a multidimensional plane according to operatingcharacteristics of the individual load apparatuses. Further, therecombining unit 1004 can be configured to map and recombine theclassified data set according to a time domain.

Prior to this, the recombining unit 1004 can be configured to decompressdata. When the energy measuring apparatus 102 transmits the compresseddata, the energy measuring apparatus 102 can cancel the data compressionin order to increase the execution speed. When the compression iscancelled, the recombining unit 1004 can be configured to map theclassified data to a power consumption change in the time domain torecombine components in the same load apparatus.

The FIG. 10 illustrates a limited overview of the energy measurementinformation labeling server 700 but, it is to be understood that otherembodiments are not limited thereto. The labels provided to each unit orcomponent is only for illustrative purpose and does not limit the scopeof the invention. Further, the one or more components can be combined orseparated to perform the similar or substantially similarfunctionalities without departing from the scope of the invention.Furthermore, the energy measurement information labeling server 700 caninclude various other components interacting locally or remotely alongwith other hardware or software components to label the extracted energyusage information of a plurality of load apparatus connected to a powerpenetration point. For example, the component can be, but is not limitedto, a process running in the controller or processor, an object, anexecutable process, a thread of execution, a program, or a computer.

FIG. 11 is a flowchart illustrating various operations performed by theenergy measurement information labeling server 700, according to theembodiments as described herein. In an embodiment, the recombining unit1004 can be configured to decompress data (Step S1102). When the energymeasuring apparatus 102 transmits the compressed data, the energymeasuring apparatus 102 can cancel the data compression in order toincrease the execution speed. The recombining unit 1004 can beconfigured to classify large classification load apparatus (Step S1104).A distribution plane is distinguished according to load operatingcharacteristics (on or off, multi-steps, a continuous change, and alwaysactivation) for the individual load apparatuses determined as the sameenergy load apparatus.

Further, the recombining unit 1004 can be configured to performclustering of features (Step S1106). The multi-dimensional plane isreconfigured so as to facilitate setting a boundary in the distributionplane by interlocking a clustering data set. In an embodiment, theactive power, the reactive power, a time, or the like can be referenceareas in reconfiguring the multi-dimensional plane.

When the multi-dimensional plane is reconfigured, the recombining unit1004 can be configured to perform machine learning (Step S1108). Theoperations of the individual load apparatuses or an inter-componentboundary classification reference is generated by using a clusteringresult for each load apparatus and a machine running method based on astatus distinguishment technique such as an artificial intelligencenetwork. In addition, the recombining unit 1004 can be configured to setspecific load apparatus classification boundary (Step S1110). Data areclassified by performing load distinguishment at an individual componentlevel for clustering data by using the machine running boundaryclassification reference. In this case, unregistered-scheme detailedload classification is determined up to component levels for theindividual load apparatuses from a total electric energy.

Further, the recombining unit 1004 can be configured to map time domain(Step S1112). The data sets for unregistered components classified inthe process are mapped to real-time data in the time domain. Therecombining unit 1004 can be configured to distinguish the mapped data(Step S1114). The mapped data are distinguished at the component levelby various colors or a display method which may be recognized by theuser.

Furthermore, the recombining unit 1004 can be configured to recombinethe same load (Step S1116). A group is generated for the load apparatuswhich may be recognized by the user by combining sub components in theindividual load apparatuses generated in the distinguishing step. As oneexample, compressor, motor, lamp, and control circuit characteristics,generated in the distinguishing step, are combined to be grouped into arefrigerator.

After the recombination step, the labeling unit 1006 can be configuredto label the recombined data set. For example, a name of a correspondingload apparatus automatically matches unregistered temporary mark dataclassified as the individual load apparatuses in association with aprestored load apparatus data set. As one example, the A, B, C, or thelike may be automatically registered as a refrigerator, a television, awashing machine, or the like through a data pattern and a matchingtechnique with storage data.

Further, in the embodiment, labeling may be manually received. In spiteof execution of automatic labeling, a developer or the user manuallynames apparatuses with respect to loads which are unregistered due tomismatching with prestored load apparatus data and inputs the names. Amethod that uses an on or off time of the apparatus is also available.

Further, the corresponding data are separately stored together withregistration with respect to the individual load apparatuses in whichthe manual labeling is performed to extend a prestored load apparatusdata set.

Furthermore, the energy measurement information labeling server 700 mayprovide data analysis information using energy usage information of theindividual load apparatuses. The data analysis based on a behavioristicpsychology analysis technique may be applied to total power and energyusage patterns of the individual load apparatuses to generate a specificdata set.

Further, a specialist consulting tip to induce energy saving of the usermay be automatically generated through the data analysis.

Moreover, an integrated service is available, which provides the totalelectric energy, usages of the individual load apparatuses, energysaving consulting, or the like to a specific building and a unithousehold through an energy IT special provider.

Example of various energy saving consulting can be, when a change of theclustering data set distinguished at the component level is sensed inassociation with the statuses of the individual load apparatuses todetermine component aging statuses or failure statuses of the individualload apparatuses, to provide the determined component aging statuses orfailure statuses to the user.

According to the embodiments, the hardware of the meter and the softwaretechniques on the server are combined to extract energy usageinformation about individual components of various load apparatuses fromtotal energy usage information at the power penetration point.

Further, since the software technique of the server is flexibly combinedwith the single energy measuring apparatus, detailed and accurate energyusage information of the individual load apparatuses is extractedwithout large cost for system installation through multiple apparatusesto derive a high-end energy saving scheme. In particular, it is possibleto acquire energy usage information higher than a branch circuit levelwithout adopting multiple sensors in the distribution board.

In summary, in the present invention, in extracting the energy usageinformation of the individual load apparatuses in the total electricenergy consumption measured at the power penetration point, a specificserver does not perform all techniques. Unlike the conventionalmechanisms, the previous information processing is performed so as tohave resolution which may be distinguished for each component in thesingle energy measuring apparatus and the server concentrativelyperforms data storage, pattern analysis, and data utilization as anadvantage thereof to secure flexibility in energy usage associated massdata processing, storing, or management of various loads.

The various actions, acts, blocks, steps, or the like of the FIG. 11 maybe performed in the order presented, in a different order orsimultaneously. Further, in some embodiments, some of the actions, acts,blocks, steps, or the like may be omitted, added, modified, skipped, orthe like without departing from the scope of the invention.

For example, FIG. 12 is a graph illustrating a probability distributionof achieving reduction for a reduction request amount depending on theamount of compensation per different unit usage estimated for eachsubscriber, according to embodiments as described herein. In the FIG.12, a horizontal axis indicates a reduction request amount and avertical axis indicates a probability of achieving the reduction requestamount. The different curves shown in the FIG. 12 indicate differentamounts of compensations per unit usage. The amount of compensation perunit usage may vary depending on a reduction request time because apower generation price varies due to a weather situation, power supplyreservation rate, or the like.

FIG. 13 a is a flowchart illustrating a method for forecasting powerconsumption based on consumption characteristics, according to theembodiments as described herein. In an embodiment, the method forforecasting power consumption, according to the exemplary embodimentincludes a power consumption element extracting step (S1310), arelationship model generating step (S1320), and a power consumptioncalculating step (S1330).

In the power consumption element extracting step (S1310), the powerconsumption for each device is segmented per time to extract at leastone power consumption element that influences the power consumption. Thedevice described herein may be, for example, a feeder that suppliespower or an apparatus consuming the power is segmented per time.

In an embodiment, the feeder which supplies the power to each electronicapparatus is configured below a power penetration point as illustratedin the FIG. 2 to supply the power. In general, there are many cases inwhich a purpose of use of the appliance is segmented per time for eachfeeder. Further, the appliance having the same purpose of use isconnected to one feeder. For example, an air-conditioner, an indoorelectric lamp, an electric heat device in an office, or the like may beused while being connected to different feeders.

In this case, in an embodiment, the power consumption may be powerconsumption of individual home appliances. The power consumption may beindirectly estimated from total power consumption except for the powerconsumption directly measured at a main power penetration point or alower feeder.

The home appliance is a combination of detailed components required foroperating the apparatus and the power consumption characteristics of theindividual home appliances. Since the respective detailed componentshave unique energy consumption characteristics, the energy consumptioncharacteristics based on an operation mode of the home appliance alsohave unique attributes. Therefore, in an embodiment, the energyconsumption characteristics are sensed based on information on thedirectly measured energy consumption. Further, the energy consumptioncharacteristics are compared with the home appliance's uniqueconsumption characteristic information to indirectly extract theoperating modes and the power consumption of the individual appliances.

When user purposes of the appliances are similar, consumption patternsare also comparatively similar. As a result, unlike the conventionalsystems and methods, real-time consumption of each device (such as thefeeder and the apparatus which consumes the power) is performed.

That is, instead of forecasting the energy consumption only based on theenergy consumption at the penetration point as illustrated in the FIG.1, in the present invention, a collection unit of energy consumptiondata is miniaturized per home appliance or feeder. A forecast elementfor each home appliance or feeder is automated and extracted andthereafter, different forecast models are applied for each homeappliance or feeder. In addition, values forecasted by the individualhome appliances or feeders are summed up to calculate a total forecastvalue.

FIG. 13 b is a flowchart illustrating various operations performed forextracting power consumption element to forecast the power consumptionbased on consumption characteristics, according to the embodiments asdescribed herein. In an embodiment, the power consumption elementextracting step (S1310) includes a power consumption segmenting step(S1312), a power consumption element extracting step (S1314), and athreshold or more power consumption element determining step (S1316).

In an embodiment, in the power consumption segmenting step (S1312), thepower consumption collected for each feeder or apparatus is segmented ata given time. That is, the power consumption is separated and collectedfor each home appliance or feeder in order to forecast the total powerconsumption. The power consumption collected and forecasted herein maybe one or more of the apparent power consumption, idle powerconsumption, and reactive power consumption. Idle or reactive power,voltage, current, high-frequency power samples, or the like arecollected to be used as an element to forecast. The collected powerconsumption is not limited to the arranged elements and may includevarious pieces of information associated with power consumption.

Further, the data collected for each home appliance or feeder aresegmented at a given time again. Below Table 1 shows energy consumptionfor each feeder which is collected per hour, according to the embodimentdescribed herein.

TABLE 1 Power consumption Serial No. Feeder No. Date Hours (Wh) 1 1 2014Feb. 1 00 1155.423 2 1 2014 Feb. 1 01 1000.329 3 1 2014 Feb. 1 021029.813 4 2 2014 Feb. 1 00 903.149 5 2 2014 Feb. 1 01 1051.256 6 2 2014Feb. 1 02 1003.607 7 3 2014 Feb. 1 00 925.750 8 3 2014 Feb. 1 011012.230 9 3 2014 Feb. 1 02 1002.596

In an embodiment, the data collected for each feeder are segmented pertime as an example, but the data may also be segmented per 30 minutes,15 minutes, or the like for a more detailed forecast. Further, thesegment unit may vary depending on the environment and the segmentationunit may vary for each time.

Further, in an embodiment, in the power consumption element extractingstep (S1314), at least one power consumption element that influences thepower consumption through the segmented power consumption is extracted.

The power consumption elements that influence the variation of the powerconsumption can include, for example, an indoor temperature, an outdoortemperature, humidity, a wind velocity, a sensory temperature, a minutedust degree, a CO₂ degree, minute dust, yellow dust, an ozone amount, aninfectious disease, time, or the like. Apart from the above the powerconsumption elements, other examples of power consumption elements whichmay influence power consumption can include number of persons whoresides in the house (which may be determined using a motion sensor or aCO₂ sensor), a specific member presence in the house (e.g., whether amember who overspends electricity stays), temperature measured using asensor (installable at several points such as a room, a kitchen, or thelike), positional information of a vehicle in the house, or the like.

Below Table 2 shows example temperature collected of an outdoor in aregion where an electricity consumption measuring device is installed.The temperatures are collected based on data of the MeteorologicalAdministration Agency.

TABLE 2 Serial No. Region code Temperature Observation time 1 108 −5.72014 Jan. 13 15:00:00 2 108 −6.2 2014 Jan. 13 16:00:00 3 108 −6.6 2014Jan. 13 17:00:00 4 108 −7.2 2014 Jan. 13 18:00:00 5 108 −7.9 2014 Jan.13 19:00:00 6 108 −8.1 2014 Jan. 13 20:00:00 7 108 −8.4 2014 Jan. 1321:00:00 8 108 −8.9 2014 Jan. 13 22:00:00 9 108 −8.6 2014 Jan. 1323:00:00

In an embodiment, in the threshold value or more power consumptionelement determining step (S1316), a correlation coefficient representinga correlation between the extracted power consumption element and thepower consumption is calculated to determine the power consumptionelement having a correlation coefficient which is a predeterminedthreshold value or more.

That is, a correlation between the power consumption for each homeappliance or feeder and the collected power consumption influenceelements is analyzed. For example, a correlation between a usage foreach time of each feeder and an outdoor temperature of the correspondingtime may be digitized by using a Pearson correlation coefficient or aSpearman correlation coefficient. In particular, based on a temperature(e.g., 15 degrees Celsius) with which persons generally feel convenientwhen calculating a correlation with a temperature, both a correlationcoefficient between a temperature which is lower than the correspondingtemperature and the power consumption; and a correlation coefficientbetween a temperature which is higher than the corresponding temperatureand the electricity consumption are calculated to set a value having ahigher absolute value as the correlation coefficient. This is used tocomplement that the Pearson correlation coefficient is 0. An examplegraph illustrating a correlation coefficient using is explained inconjunction with the FIG. 14 (in the case of the temperature). Further,a relationship between the power consumption for each feeder and thetemperature are explained in conjunction with the FIG. 15.

Further, in the threshold value or more power consumption elementdetermining step (S1316), an absolute value of the correlationcoefficient for each feeder or home appliance is compared with apredetermined threshold value. For example, when the predeterminedthreshold value is 0.5, the temperature is selected as forecast elementsof feeders 9 and 10 as shown in the FIG. 15. When a forecast elementthat exerts a large influence on a demand of a specific feeder or homeappliance is found in advance, the correlation calculating step may beomitted with respect to the corresponding feeders or home appliances.

According to the aforementioned exemplary embodiment, in the powerconsumption element extracting step (S1310), the one or more powerconsumption elements for all feeders or home appliances are extracted.

Further, the relationship model generating step (S1320) according to theembodiment will be described. In an embodiment, in the relationshipmodel generating step (S1320), a relationship model representing therelationship between the power consumption summed up for each extractedpower consumption element and the power consumption element isgenerated.

That is, usages of the feeders or home appliances having the same powerconsumption element are all summed up under a given time unit. When thespecific feeder or home appliance has a unique characteristic, theusages are not summed up but only the usage of the corresponding feederor home appliance may be separately considered. In an embodiment, if asingle function cannot be obtained from any singularity due to a deviceof unique characteristic of energy consuming, another function may begenerate for the singular device in addition to the general function toenhance the relationship.

Further, the summed-up value may be log-converted or the primitive valuemay be used as it is. Below Table 3 shows a log conversion value of atotal usage of the feeders that sensitively react to the externaltemperature at 10 A.M. on weekdays and an external temperaturemeasurement value.

TABLE 3 log External Serial No. Observation time (consumption + 1)temperature 1 2014 Feb. 3 10:00:00 9.206443 −2.7 2 2014 Feb. 4 10:00:009.131649 −8.7 3 2014 Feb. 5 10:00:00 9.134958 −6.4 4 2014 Feb. 610:00:00 9.141014 −2.5 5 2014 Feb. 7 10:00:00 8.916719 1.2 6 2014 Feb.10 10:00:00 8.824727 0.4 7 2014 Feb. 11 10:00:00 7.909074 −0.3 8 2014Feb. 12 10:00:00 8.114223 1.7 9 2014 Feb. 13 10:00:00 8.756215 1.4

Further, in the relationship model generating step (S1320) according tothe embodiment, among models that may describe the relationship betweenthe power consumption and the forecast element, a model having a highestdescription degree of data is selected and a corresponding modelcoefficient is extracted from the data. For example, the log conversionvalue of the total usage of the feeders that sensitively react to theexternal temperature may expressed as a quadric polynomial function ofthe external temperature and a coefficient of the corresponding modelmay be calculated through a least square method, or the like.

The various actions, acts, blocks, steps, or the like of the FIG. 3 maybe performed in the order presented, in a different order orsimultaneously. Further, in some embodiments, some of the actions, acts,blocks, steps, or the like may be omitted, added, modified, skipped, orthe like without departing from the scope of the invention.

FIG. 14 is a diagram illustrating an example of calculating acorrelation coefficient, according to the embodiments as describedherein. In an embodiment, this is used to complement that the Pearsoncorrelation coefficient is 0 in a usage graph having a form asillustrated in the FIG. 14 in the case of the temperature.

FIG. 15 is a diagram illustrating a relationship between the powerconsumption for each feeder and a temperature, according to theembodiments as described herein. In an embodiment, an externaltemperature of a predetermined building and a usage for each feeder areshown in the graph and the Pearson correlation coefficient is recorded.Only the data of 15 degrees Celsius or less is used and only usage datain a business time period (9 A.M. to 6 P.M.) during the week areconsidered by using a characteristic (in that the predetermined buildingis an office building). Herein, as the usage for each feeder, a logconverted value (log (power consumption+1)) is used, but a primitivevalue which is not converted may also be directly used.

FIG. 16 is a diagram illustrating an example for estimating therelationship between the power consumption and the temperature,according to the embodiments as described herein. In an embodiment, aresult of estimating log conversion values of the external temperatureand the usage according to the quadric polynomial function aredescribed. B-Spline, or the like may be used for estimation in additionto the polynomial function. When the one or more power consumptionelements are available, multi-dimensional surface estimation may beperformed by using the polynomial function or the B-Spline function, orthe like.

A residual between a value calculated in each relationship model and anactual observation value is named as a virtual feeder or home applianceand, thereafter, may be modeled while being considered as a separatefeeder or home appliance in modeling through time-series analysis to bedescribed below.

Usage of all feeders or home appliances in which the power consumptionelement is not extracted may be all summed up and modeled by using thetime-series analysis methods such as Exponential smoothing,Autoregressive Integrated Moving Average (ARIMA), functional analysis,or the like. When the specific feeder or home appliance has a peculiarattribute for the time, the corresponding extracted power consumptionelements may not be summed up and may be separately modeled.

FIG. 17 is a diagram illustrating a modeling example, according to theembodiments as described herein. In an embodiment, an example ofmodeling a sum total of feeders without another forecast element otherthan the time by using a Double seasonal Holt-Winters method isdescribed. In the method for forecasting the power consumption, therelationship models used for the forecast may be made into a database(stored in advance) and the power consumption may be forecasted byreceiving the relationship model. Further, the generated relationshipmodel may be learnedly updated according to an error value.

FIG. 18 is a flowchart illustrating a method for forecasting powerconsumption, according to another exemplary embodiment of the presentinvention. In an embodiment, the method may include a relationship modelinputting step (S1802), a power consumption calculating step (S1330),and a forecast information providing step (S1804).

That is, in the relationship model inputting step (S1802), therelationship model generated through the power consumption elementextracting step (S1310) and the relationship model generating step(S1320) according to the aforementioned embodiment is the input.

Further, in the power consumption calculating step (S1330), the powerconsumption is calculated through the input relationship model. In theforecast information providing step (S1804), additional informationbased on the calculated power consumption is provided. That is, in anembodiment, in the forecast information providing step (S1804) as a stepof providing the calculated power consumption, the energy consumption isforecasted for each time and values after a predetermined time (e.g.,after 24 hours) are summed up to present a forecast value for each date.

Further, as additional information, a cumulative usage or a powerconsumption peak time may be notified in advance. That is, a forecastsystem manager or a forecast system user foretells a reach time of apredetermined cumulative usage. For example, when the cumulative usageof the corresponding month belongs to cumulative step 1 of a personalhousehold at present and entrance of cumulative step 2 is anticipatedafter three days, this may be notified in advance. Further, a maximumvalue of a usage per hour on a next day and a time interval in which thecorresponding maximum value is generated may be notified in advance.

As additional information, an abnormal symptom of the home appliance maybe supposed and notified. That is, in the present invention, the energyconsumption for each feeder or home appliance is forecasted. When anactual usage of the specific feeder or home appliance is excessivelydifferent from a forecast value, it may be notified that an error occursin at least one of the corresponding home appliance or at least one ofhome appliances connected to the corresponding feeder.

Herein, the excessive difference may be defined as a case in which anabsolute value of a difference between a forecast value Pi and an actualobservation value Oi is larger than a value acquired by multiplying astandard deviation σ of the observed value by a predetermined value θ(|Pi−Oi|>θ×σ) as described below. In this case, the forecast value andthe observed value are log-converted to be compared. When the forecastvalue and the observed value of the power consumption are compared witheach other, one or more of apparent power consumption, idle powerconsumption, and reactive power consumption may be compared with eachother.

Values at one moment are compared to notify the abnormal symptom, butwhen Si defined, as below, is equal to or more than a predeterminedvalue by using a cumulative summation chart (CUSUM), the abnormalsymptom may be notified.

$\begin{matrix}{{S_{i} = {\max ( {{S_{i} + l_{i}},0} )}},{l_{i} = {{\log ( {P( {d =  d_{i} \middle| {abnormal} } )} )} - {\log ( {P( {d =  d_{i} \middle| {normal} } )} )}}},{d_{i} = \{ \begin{matrix}1 & {{{{if}{{P_{i} - O_{i}}}} > {\theta\sigma}},} \\0 & {{otherwise}.}\end{matrix} }} & \lbrack {{Equation}\mspace{14mu} 1} \rbrack\end{matrix}$

Herein, P (d=1|abnormal) and P (d=1|normal) and respective probabilitiesare values calculated in the previous observation or a prior knowledge.

An apparatus that performs the method for forecasting the powerconsumption based on the consumption characteristics according to theexemplary embodiment may be configured as illustrated in the FIG. 19.

The various actions, acts, blocks, steps, or the like of the FIG. 18 maybe performed in the order presented, in a different order orsimultaneously. Further, in some embodiments, some of the actions, acts,blocks, steps, or the like may be omitted, added, modified, skipped, orthe like without departing from the scope of the invention.

The FIG. 19 is a block diagram illustrating an apparatus 1900 forforecasting power consumption based on consumption characteristics,according to the embodiments as described herein. In an embodiment, theapparatus 1900 includes a power consumption element extracting unit1902, a relationship model generating unit 1904, and a power consumptioncalculating unit 1906.

In an embodiment, in the power consumption element extracting unit 1902,a power consumption segmenting unit 1908 is configured to segment powerconsumption for each feeder that supplies power for each apparatus thatconsumes the power per time, an influence element extracting unit 1910configured to extract at least one power consumption element thatinfluences power consumption, and a power consumption elementdetermining unit 1912 configured to determine a power consumptionelement which is equal to or more than a threshold value. Therelationship model generating unit 1904 is configured to generate arelationship model representing the relationship between powerconsumption summed up for each extracted power consumption element andthe power consumption element. The power consumption calculating unit1906 is configured to calculate the power consumption through thegenerated relationship model.

Further, although not illustrated, the apparatus 1900 may be constitutedby a relationship model inputting unit receiving a relationship modelstored in a separate database, a power consumption calculating unitcalculating the power consumption through the relationship model inputunit, and a forecast information providing unit providing informationthrough the calculated power consumption.

The FIG. 19 illustrates a limited overview of the apparatus 1900 forforecasting the power consumption based on consumption characteristicsbut, it is to be understood that other embodiments are not limitedthereto. The labels provided to each unit or component is only forillustrative purpose and does not limit the scope of the invention.Further, the one or more modules can be combined or separated to performthe similar or substantially similar functionalities without departingfrom the scope of the invention. Furthermore, the apparatus 1900 caninclude various other components interacting locally or remotely alongwith other hardware or software components to forecast the powerconsumption based on consumption characteristics. For example, thecomponent can be, but is not limited to, a process running in thecontroller or processor, an object, an executable process, a thread ofexecution, a program, or a computer.

The foregoing description of the specific embodiments will so fullyreveal the general nature of the embodiments herein that others can, byapplying current knowledge, readily modify or adapt for variousapplications such specific embodiments without departing from thegeneric concept, and, therefore, such adaptations and modificationsshould and are intended to be comprehended within the meaning and rangeof equivalents of the disclosed embodiments. It is to be understood thatthe phraseology or terminology employed herein is for the purpose ofdescription and not of limitation. Therefore, while the embodimentsherein have been described in terms of preferred embodiments, thoseskilled in the art will recognize that the embodiments herein can bepracticed with modification within the technical spirit and scope of theembodiments as described herein.

What is claimed is:
 1. A method for forecasting power consumption basedon consumption characteristics, the method comprising: segmenting, by apower consumption element extracting unit, power consumption for eachdevice per time to extract at least one power consumption element thatinfluences said power consumption, wherein said device is at least oneof a feeder that supplies power and an appliance consuming power;generating, by a relationship model generating unit, a relationshipmodel representing a relationship between a sum of power consumption foreach said extracted power consumption element and a power consumptionelement; and calculating, by a power consumption calculating unit, apower consumption based on said generated relationship model.
 2. Themethod of claim 1, wherein extraction of said power consumption elementcomprises: calculating a correlation coefficient representing acorrelation between said extracted power consumption element, and saidpower consumption; and determining said power consumption element basedon said correlation coefficient, wherein said correlation coefficient isat least one of a predetermined threshold value and more than saidthreshold value.
 3. The method of claim 1, wherein generating saidrelationship model comprises: determining said sum of said powerconsumption by each extracted power consumption element; and generatingsaid relationship model representing relationship between said sum ofpower consumption for each said extracted power consumption element, andsaid power consumption element.
 4. The method of claim 1, wherein saidrelationship model is separately generated for each said device having aunique characteristic.
 5. The method of claim 1, wherein saidrelationship model is generated for said device by summing up said powerconsumption for said device in which said power consumption element isnot extracted.
 6. The method of claim 2, wherein said correlationcoefficient is calculated using one of a Pearson correlation coefficientand a Spearman correlation coefficient.
 7. The method of claim 1,wherein said sum of power consumption for each said extracted powerconsumption element is expressed as a polynomial function for saidextracted power consumption element, wherein a coefficient for saidpolynomial function is calculated through a minimum square method togenerate said relationship model.
 8. The method of claim 1, wherein saidsum of power consumption for each said extracted power consumptionelement is expressed as a B-spline function to generate saidrelationship model.
 9. The method of claim 5, wherein said relationshipmodel is generated by performing one of exponential smoothing,Autoregressive Integrated Moving Average (ARIMA), functional analysis,and a time series analysis method with respect to said sum of powerconsumption for each said extracted power consumption element.
 10. Amethod for generating a forecast model of power consumption based onconsumption characteristics, the method comprising: segmenting powerconsumption for each feeder that supplies power per time; extracting atleast one power consumption element that influences power consumptionthrough said segmented power consumption; calculating a correlationcoefficient representing a correlation between said extracted powerconsumption element and said power consumption; determining a powerconsumption element, from said extracted power consumption element,based on said correlation coefficient, wherein said correlationcoefficient is at least one of a predetermined threshold value and morethan said threshold value; summing up said power consumption for eachsaid power consumption element having said correlation coefficient; andgenerating a relationship model representing a relationship between saidextracted power consumption element and said summed-up powerconsumption.
 11. A method for forecasting power consumption based onconsumption characteristics, the method comprising: segmenting, powerconsumption for each device per time to extract at least one powerconsumption element that influences said power consumption, wherein saiddevice is at least one of a feeder that supplies power and an applianceconsuming power; receiving a relationship model representingrelationship between a sum of power consumption for each said extractedpower consumption element, and a power consumption element; andcalculating said power consumption based on said received relationshipmodel.
 12. The method of claim 11, further comprising providingadditional information based on said calculated power consumption. 13.An apparatus for forecasting power consumption based on consumptioncharacteristics, the apparatus comprising: a power consumption elementextracting unit configured to power consumption for each device per timeto extract at least one power consumption element that influences saidpower consumption, wherein said device is at least one of a feeder thatsupplies power and an appliance consuming power; a relationship modegenerating unit configured to generate a relationship model representinga relationship between a sum of power consumption for each saidextracted power consumption element, and a power consumption element;and a power consumption calculating unit configured to calculate saidpower consumption based on said generated relationship model.
 14. Anapparatus for forecasting power consumption based on consumptioncharacteristics, the apparatus comprising: a relationship modelinputting unit configured to segment power consumption for one of eachfeeder that supplies power per time and appliance that consumes powerper time to receive a relationship model representing the relationshipbetween power consumption summed up for each at least one powerconsumption element that influences said extracted power consumption andsaid power consumption element; a power consumption calculating unitcalculating said power consumption through said received relationshipmodel; and a forecast information providing unit providing additionalinformation based on said calculated power consumption.